Zachary Depp, Halit Bugra Tulay, C. Emre Koksal (The Ohio State University)

The traditional vehicular roll-jam attack is an effective means to gain access to the target vehicle by jamming and recording key fob inputs from a victim. However, it requires specific knowledge of the attack surface, and delicate tuning of software-defined radio parameters. We have developed an enhanced version of the roll-jam attack that uses a known noise signal for jamming, in contrast to the additive white Gaussian noise that is typically used in the attack. Using a known noise signal allows for less strict tuning of the software-defined radios used in the attack, and allows for digital noise removal of the recorded input to enhance the replay attack.

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Hugo Jonker (Open University Netherlands), Stefan Karsch (TH Koln), Benjamin Krumnow (TH Koln), Godfried Meesters (Open University Netherlands)

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Ahmed Abdo, Sakib Md Bin Malek, Xuanpeng Zhao, Nael Abu-Ghazaleh (University of California, Riverside)

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Securing Automotive Software Supply Chains (Long)

Marina Moore, Aditya Sirish A Yelgundhalli (New York University), Justin Cappos (NYU)

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Runhao Li (National University of Defense Technology), Bin Zhang (National University of Defense Technology), Jiongyi Chen (National University of Defense Technology), Wenfeng Lin (National University of Defense Technology), Chao Feng (National University of Defense Technology), Chaojing Tang (National University of Defense Technology)

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